Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds real value beyond that: it names the data-source coverage (World Bank, FRED, Eurostat, OECD, IMF, WHO, ECB, US Census, SEC) and the fact that it works on any verified autario indicator, which tells the agent the input domain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the operation and its output fields, then the usage directive, then the source coverage. Every sentence carries information and none is redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, but the description compensates by enumerating the returned statistics, and the schema fully documents the parameters. Combined with annotations that cover the safety profile, nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all three parameters (indicator, entity, time) are already fully documented in the schema, including the time-window parsing rules. The description adds only the 'single indicator+entity' scoping, which is already implied by the required parameters, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific operation (summary statistics) on a specific resource (a single indicator+entity series) and enumerates exactly what is computed (n, mean, median, std, min/max, quartiles, skew, histogram). This clearly separates it from statistical siblings like correlate, regression, rolling_stats, and calculate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells the agent when to reach for it: 'Use FIRST before running any test so you know what the data looks like', with the rationale (sample size, completeness, distribution shape). It stops short of naming a specific alternative tool or stating when-not to use it, so it falls just below the top tier.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.